- In this paper, we present a multi-level recognizer for on- line Arabic handwriting. In Arabic script (handwritten and printed), cursive writing - is not a style - it is an inher- ent part of the script. In addition, the connection between letters is done with almost no ligatures, which complicates segmenting a word into individual letters. In this work, we have adoptedthe holistic approachand avoided segmenting wordsinto individualletters. To reducethesearchspace, we applya series offilters in ahierarchicalmanner. Theearlier filters perform light processing on a large number of candi- dates, and the later filters perform heavy processing on a small number of candidates. In the first filter, global fea- tures and delayed strokes patterns are used to reduce can- didate word-part models. In the second filter, local features are used to guide a dynamic time warping (DTW) classifi- cation. The resulting k top ranked candidates are sent for shape-context based classifier, which determines the recog- nized word-part. In this work, we have modified the classic DTW to enable different costs for the different operations and control their behavior. We have performed several ex- perimental tests and have received encouraging results.